Multiplex PageRank.
Multiplex PageRank.
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DOI：
10.1371/journal.pone.0078293
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发表时间：
2013
期刊：
影响因子：
3.7
通讯作者：
Bianconi G
中科院分区：
文献类型：
--
作者：
Halu A;Mondragón RJ;Panzarasa P;Bianconi G
许多复杂系统可以描述为多个网络，其中相同的节点可以在不同的层次上相互作用，从而形成一组相互作用和共同进化的网络。这种多路系统的例子是社交网络，其中人们参与不同类型的关系，并通过各种形式的通信媒体进行交互。复杂网络中节点的排序是当前复杂网络研究面临的最紧迫和最具挑战性的任务之一。当节点对可以通过多个链路和多个层连接时，节点的排序必须反映一个层中节点的重要性以及它们在其他相互依赖的层中的重要性。本文利用有偏随机游走的思想定义了多重PageRank中心性度量，该度量直接考虑了网络之间的相互作用对节点中心性的影响。特别是，根据层之间交互的强度，我们定义了多路复用PageRank的加法、乘法、组合和中性版本，并展示了每个版本如何反映一个层中的节点的重要性对该节点在另一层中可以获得的重要性的影响程度。我们讨论了这些措施，并将它们应用到一个在线多元社交网络中。研究结果表明，考虑到网络的多路性质有助于发现不同于从单个层获得的排名的节点排名的出现。结果支持多路中心性测量的显著程度，如多路复用PageRank，用于评估嵌入在多个交互网络中的节点的显著程度，并提供关于结构特性的新的光，否则如果孤立地分析每个交互网络，这些结构特性将保持不被检测到。
Many complex systems can be described as multiplex networks in which the same nodes can interact with one another in different layers, thus forming a set of interacting and co-evolving networks. Examples of such multiplex systems are social networks where people are involved in different types of relationships and interact through various forms of communication media. The ranking of nodes in multiplex networks is one of the most pressing and challenging tasks that research on complex networks is currently facing. When pairs of nodes can be connected through multiple links and in multiple layers, the ranking of nodes should necessarily reflect the importance of nodes in one layer as well as their importance in other interdependent layers. In this paper, we draw on the idea of biased random walks to define the Multiplex PageRank centrality measure in which the effects of the interplay between networks on the centrality of nodes are directly taken into account. In particular, depending on the intensity of the interaction between layers, we define the Additive, Multiplicative, Combined, and Neutral versions of Multiplex PageRank, and show how each version reflects the extent to which the importance of a node in one layer affects the importance the node can gain in another layer. We discuss these measures and apply them to an online multiplex social network. Findings indicate that taking the multiplex nature of the network into account helps uncover the emergence of rankings of nodes that differ from the rankings obtained from one single layer. Results provide support in favor of the salience of multiplex centrality measures, like Multiplex PageRank, for assessing the prominence of nodes embedded in multiple interacting networks, and for shedding a new light on structural properties that would otherwise remain undetected if each of the interacting networks were analyzed in isolation.
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多路复用网络中合作的演变。
影响因子：
4.6
作者：
Gomez-Gardenes, Jesus;Reinares, Irene;Arenas, Alex;Mario Floria, Luis
通讯作者：
Mario Floria, Luis
DOI：
10.1108/s0882-6145(2010)0000027012
发表时间：
2010-01-01
期刊：
ADVANCES IN GROUP PROCESSES
影响因子：
--
作者：
Kuwabara, Ko;Luo, Jiao;Sheldon, Oliver
通讯作者：
Sheldon, Oliver
DOI：
10.1073/pnas.1110586109
发表时间：
2012-03-20
影响因子：
11.1
作者：
Brummitt, Charles D.;D'Souza, Raissa M.;Leicht, E. A.
通讯作者：
Leicht, E. A.
影响因子：
4.9
作者：
Ferriani, Simone;Fonti, Fabio;Corrado, Raffaele
通讯作者：
Corrado, Raffaele
影响因子：
2.4
作者：
Gomez-Gardenes, Jesus;Latora, Vito
通讯作者：
Latora, Vito